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Mastering TensorFlow 1.x

You're reading from   Mastering TensorFlow 1.x Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788292061
Length 474 pages
Edition 1st Edition
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Table of Contents (21) Chapters Close

Preface 1. TensorFlow 101 2. High-Level Libraries for TensorFlow FREE CHAPTER 3. Keras 101 4. Classical Machine Learning with TensorFlow 5. Neural Networks and MLP with TensorFlow and Keras 6. RNN with TensorFlow and Keras 7. RNN for Time Series Data with TensorFlow and Keras 8. RNN for Text Data with TensorFlow and Keras 9. CNN with TensorFlow and Keras 10. Autoencoder with TensorFlow and Keras 11. TensorFlow Models in Production with TF Serving 12. Transfer Learning and Pre-Trained Models 13. Deep Reinforcement Learning 14. Generative Adversarial Networks 15. Distributed Models with TensorFlow Clusters 16. TensorFlow Models on Mobile and Embedded Platforms 17. TensorFlow and Keras in R 18. Debugging TensorFlow Models 19. Tensor Processing Units
20. Other Books You May Enjoy

TF Slim

TF Slim is a lightweight library built on top of TensorFlow core for defining and training models. TF Slim can be used in conjunction with other TensorFlow low level and high-level libraries such as TF Learn. The TF Slim comes as part of the TensorFlow installation in the package: tf.contrib.slim. Run the following command to check if your TF Slim installation is working:

python3 -c 'import tensorflow.contrib.slim as slim; eval = slim.evaluation.evaluate_once'

TF Slim provides several modules that can be picked and applied independently and mixed with other TensorFlow packages. For example, at the time of writing of this book TF Slim had following major modules:

TF Slim module Module description
arg_scope Provides a mechanism to apply elements to all graph nodes defined under a scope.
layers Provides several different kinds of layers such as fully_connected...
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Mastering TensorFlow 1.x
Published in: Jan 2018
Publisher: Packt
ISBN-13: 9781788292061
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